Changes in the utilisation of acute hospital care in Ireland during the first wave of the COVID-19 pandemic in 2020 [version 2; peer review: 1 approved, 2 approved with reservations]

Background: Reduced and delayed presentations for non-COVID-19 illness during the COVID-19 pandemic have implications for population health and health systems. The aim of this study is to quantify and characterise changes in acute hospital healthcare utilisation in Ireland during the first wave of COVID-19 to inform healthcare system planning and recovery. Methods: A retrospective, population-based, observational study was conducted using two national datasets, Patient Experience Time (PET) and Hospital In-Patient Enquiry (HIPE). The study period was 6th January to 5th July 2020. Results: Comparison between time periods pre- and post-onset of the COVID-19 pandemic within 2020 showed there were 81,712 fewer Emergency Department (ED) presentations (-18.8%), 19,692 fewer admissions from ED (-17.4%) and 210,357 fewer non-COVID-19 hospital admissions (-35.0%) than expected based on pre-COVID-19 activity. Reductions were greatest at the peak of population-level restrictions, at Discussion: While public health implications of delayed and lost care will only become fully apparent over time, recovery planning must begin immediately. In the short-term, backlogs in care need to be managed and population health impacts of COVID-19 and associated restrictions, particularly in relation to mental health and alcohol, need to be addressed through strong public health and health system responses. In the long-term, COVID-19 highlights health system weakness and is an opportunity to progress health system reform to deliver a universal, high-quality, sustainable and resilient health system, capable of meeting population health needs and responding to future pandemics. This is an interesting study showing some of the impacts of the pandemic on the Irish Health System. Whereas the authors have already addressed many issues raised by the other reviewers, an overall lack of context remains. The data sets used are from public hospitals only. One positive outcome of the pandemic was the use of private hospitals. They took over much of the elective and non-covid hospital care from the public hospitals. Whereas there is a mention in the limitations of the study, it should be better reflected in the whole manuscript. Reductions in non-covid admissions in the data may just be because these admissions happened in the private hospitals, not necessarily because they did not happen. This should be discussed in the results. It is now presented as if there just is a reduction due to the pandemic, which is true, but not the whole story. The reduction of 35% in non-covid admissions may be entirely explained by redirecting these to private hospitals. The term recovery period is not appropriate. By July 2020 there was no recovery, in either healthcare use, the pandemic or otherwise. Please choose a better term throughout (or just stick with period 4). This population-based study described the utilization of acute hospital services during the first wave of the COVID-19 pandemic in Ireland. The study was based on two national databases; ED attendances were obtained from Patient Experience Time (PET), while acute hospital discharge data were derived from Hospital In-Patient Enquiry (HIPE). Descriptive statistics and regression analysis were used to compare presentation to and admission from ED and acute hospital admission of any type for a non-COVID-19 illness across the four study periods, representing the epidemiology and public health management of COVID-19 in Ireland. This study shows that the first wave of COVID-19 was associated with decreased ED presentations, fewer admissions from ED, and non-COVID-19 hospital admissions. does study assessed the impact of pandemic and the public health and health system measures on health care did not how changes in health care utilization may


Introduction
The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), presents a significant challenge to national health systems across the globe. In addition to controlling the transmission of infection across the population and ensuring sufficiency of health services to meet demand, impacts on the provision of non-COVID-19 care are reported in many countries 1,2 . Internationally, reduced and delayed presentations for non-COVID-19 illness are linked to increased morbidity and mortality [3][4][5] . These changes in utilisation of healthcare have public health implications for both population health and health systems in the short term and beyond 2 .
Ireland has faced these direct and indirect impacts of COVID-19 from a unique position. A decade ago, the Irish health system experienced severe cutbacks during a prolonged period of financial austerity 6 . Since 2017, a significant programme of reform entitled Sláintecare has been adopted by government 7-9 . Sláintecare is a ten-year plan for systemic health reform which seeks to tackle long-recognised health system capacity deficits and fragmentation, Ireland's over-reliance on acute hospital services, poor orientation to primary, community care services and public health, underpinned by the absence of universal access to health and social care 7,10 .
The aim of this study is to describe and quantify the impact of the first wave of the COVID-19 pandemic on acute healthcare utilisation in Ireland in order to inform healthcare system planning and public health policy. This work is situated within a broader research project which is co-producing research and evidence to inform health system and policy decisions 11 . The data and analysis presented here is part of the Foundations' Living Implementation Framework with Evaluation (LIFE) 11 .

Study design and setting
A retrospective, population-based, observational study was conducted to quantify and characterise acute hospital service utilisation events in Ireland and to compare these events across different time periods with reference to the epidemiology and public health management of COVID-19. Emergency Department (ED) presentations, admissions from ED and non-COVID-19 in-patient admissions to Health Service Executive (HSE) acute hospitals over a 26-week period from 6 th January 2020 to 5 th July 2020 were identified, analysed and compared with those observed over defined reference periods.

Data sources Patient Experience Time (PET).
National data ED attendances were obtained from the Patient Experience Time (PET) dataset which is an administrative dataset that contains observations of individual-level ED utilisation across 30 HSE-operated or funded hospitals 12 . PET contains information on age, sex, discharge destination, mode of arrival and referral and triage status. Clinical information is not reported and therefore patients with and without COVID-19 were included in the data used for this study. PET data does not include Minor Injury Units (MIU), private EDs, specialist EDs or direct attendance at acute assessment units.

Hospital In-Patient Enquiry (HIPE).
National acute hospitals discharge data were accessed from the Hospital In-Patient Enquiry (HIPE) data via the Health Intelligence Unit (HIU) Health Atlas Ireland Analyser. HIPE is managed by the Healthcare Pricing Office (HPO) and is a well-established, quality-assured health information system that is the primary source of episode-based, aggregate clinical, demographic and administrative data on discharges from acute public hospitals in Ireland 13 . It contains information on age, sex, area of residence, admission type, date of admission and discharge along with principal diagnosis coded using the International Classification of Diseases Tenth Revision (ICD-10) 14, 15 . It is used nationally to inform healthcare planning, management and activity-based funding 16 .

Variables
Exposure. The exposure was to COVID-19 and the associated public health restrictions and wider socioeconomic changes within 2020. The study period was divided into four sub-periods (Table 1). These time periods reflect levels of exposure based on the a priori knowledge of the epidemiology of COVID-19 during the first wave, and of the public health measures implemented. Period 1 was defined as prior to the beginning of the first wave, Periods 2 and 3 were periods where progressive public health restrictions were implemented and Period 4 commenced with the easing of public health restrictions.

Amendments from Version 1
The title of the article has been changed to Changes in the utilisation of acute hospital care in Ireland during the first wave of the COVID-19 pandemic in 2020. This is an accurate reflection of what this study achieved.
The description of the study design has been updated in the methodology to describe the study as a retrospective, population-based, observational study. This study compares population rates of healthcare utilisation during different specified time periods during the first wave of the COVID-19 pandemic in Ireland and the term interrupted time-trend analysis has been removed from the methodology.
In the methodology, there is further description of the purpose of the "tracer diagnoses" to explore trends further for selected clinical conditions to inform and aid recovery planning. The methodology has also been updated to emphasise that the Hospital In-Patient Enquiry (HIPE) data are aggregate, episodebased data and logistic regression analysis using this data was not possible. Patient Experience Time (PET) data were used in the binary logistic regression analysis to assess the factors associated with admission from an Emergency Department (ED) following an ED presentation. The manuscript states that the purpose of the regression was specifically to assess if presentation in the post-COVID-19 time periods was associated with an increased likelihood of hospital admission from ED.
The discussion has been updated to emphasise the key findings in relation to changes in elective non-COVID-19 acute hospital healthcare utilisation with expansion of the discussion in the reasons for changes in healthcare utilisation section. The manuscript now states that the findings of this paper were communicated nationally to the Health Service Executive in Ireland's leads for Integrated Care and Acute Hospitals and to the Director of Sláintecare (Ireland's policy for health service reform) to inform recovery planning from the COVID-19 pandemic.
Any further responses from the reviewers can be found at the end of the article Period 1 was defined as starting on the first Monday of January for the study period and reference periods, which were divided into the same sub-periods. The historic reference period for the PET data was a 26-week time period beginning on the first Monday of January 2019. This dataset has increased in completeness year-on-year so restricting the reference period to 2019 allowed meaningful comparison. The historic reference period for the HIPE data was a 26-week time period beginning on the first Monday in January for 2017-2019. It was assumed that while there might be a slight variation year on year, the three-year average of hospital admissions would provide meaningful comparison 13 . For analysis within 2020, the reference period was Period 1 which was prior to the beginning of the first COVID-19 wave. To compare population rates of healthcare utilisation between pre-and post-COVID-19 time periods, two reference periods were used; the historic reference periods and Period 1 2020. The results reported in this paper primarily focus on the comparison within 2020 using Period 1 2020 as a reference period.
Outcomes. The outcomes were presentation to and admission from ED as recorded on PET and an acute hospital admission of any type for a non-COVID-19 illness. A non-COVID-19 hospital admission was defined as a hospital discharge (including death) recorded on HIPE where the diagnosis was a non-COVID-19 illness. Patients recorded with an ICD-10 diagnostic code for COVID-19 (U071 OR U072 OR B342 OR B972) were excluded for this purpose. The occurrence and characteristics of the outcomes were compared between exposure and reference periods. In order to describe stratified rates of each outcome and the characteristics of the population who experienced outcomes for the exposure and reference periods, relevant variables were included from the PET and HIPE datasets ( Table 2). To explore trends further for selected clinical conditions to inform and aid recovery planning, 'tracer diagnoses' were chosen from within HIPE using defined ICD-10 codes (Table 3). These conditions were chosen following a review of the literature and from discussions with the HSE Lead for Integrated Care, for the Acute Hospitals and for Mental Health all of whom were providing frontline clinical care. The purpose of selecting the 'tracer diagnoses' was to explore healthcare utilisation trends in key clinical areas where changes in healthcare utilisation had been observed. The rationale for the selection of the 'tracer diagnoses' is outlined in Table 3.

Data analysis
Using Census 2016 data as the denominator 17 , overall, agespecific and gender-specific population rates for each outcome were calculated with 95% Confidence Intervals (CI) for weekly counts across the 26-week study period and total and average weekly counts across the defined sub-periods. Rate differences with 95% CIs, and rate ratios with 95% CIs were used to compare the occurrence of the outcome across exposure and reference periods. A chi-squared test was used to test the hypothesis that there was no difference between the proportion of the population who experienced an outcome across exposure and reference periods. The characteristics of those who experienced an outcome were compared between exposure period and reference periods using a chi-squared test to investigate the null hypothesis that there was no difference in the characteristics across exposure and reference periods. Using PET data, the effect of patient-level characteristics, including time period, were compared for association with the likelihood of admission from ED using a binary logistic regression model. Adjusted Odds Ratios (AOR) were calculated to measure the independent likelihood of admission from ED for a specific level of a characteristic relative to the reference level within the model. The purpose of the regression analysis was to assess if presentation to ED within the specific study time periods was associated with an increased likelihood of admission from ED as admission following ED presentation is an indicator of acuity 27 . The multiple logistic regression analysis could only be conducted using PET data as HIPE data are aggregate data and therefore regression analysis was not suitable. Within HIPE, initial data analysis was for all admission types, which was followed by further sub-group analysis of rates of elective and emergency non-COVID-19 hospital admissions by diagnostic group (CCS-IM) 28 . All statistical analysis was carried out using Microsoft Excel, SPSS version 26.0, Stata 15 (Stata Corporation) and Open-Source Epidemiologic Statistics for Public Health version 3.01. Level of significance for all group differences in this study was set at 5% (p-value <0.05).

Reporting guideline
The Reporting of Studies Conducted using Observational Routinely-collected Data (RECORD) guideline extended from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement on reporting guidelines was used for this study.

Ethical approval
Ethical review was not required for this study as the research is secondary analysis of anonymised data sets. The data used in the study are controlled by the HSE in Ireland. The study authors (LM and PK) conducted data processing for the study at the HSE National Health Intelligence Unit to inform the statutory function of the HSE in Ireland to improve, promote and protect the health and welfare of the public health 29 . HIPE data are anonymised for users and usual practices regarding statistical disclosure control were applied.

Results
This paper primarily focuses on the results of the comparison between Periods 2-4 2020 and Period 1 2020. It also presents key comparisons using historic reference periods. The results of the internal comparison were reviewed against the historic reference period for both PET (2019) and HIPE (2017-2019) datasets and the results and public health implications are similar. Using both reference periods demonstrated that the overall trends in healthcare utilisation were similar despite seasonal differences for comparisons made within 2020.
Overall trends -total population, gender and age group There was a substantial reduction in population rates of ED presentation and admission from ED in Periods 2-4 2020 compared to the historic reference period in 2019 ( Figure 1 and Figure 2). Similarly, there were reductions in non-COVID-19 admissions of all types compared to historic reference periods from 2017-2019. As the reductions in non-COVID-19 hospital admissions were predominantly for elective and emergency admissions and as there were notable differences Acute MI unspecified I21.9 Evidence internationally within the literature of reduced and delayed presentations with STEMI/NSTEMI and increases in morbidity and mortality 4,21-23 Self-harm X60-X84 Some evidence nationally within the literature of an initial reduction in presentations with self-harm followed by a rebound increase with increasing severity of presentations 24 Acute alcohol related presentations There is limited evidence of the impact of population level restrictions and the COVID-19 pandemic on alcohol related presentations. There is evidence that presentations with self-harm had higher rates of associated substance misuse 24 Injury S00-S99

T00-T31
Evidence that presentations due to injuries reduced during the population level restrictions due to the COVID-19 pandemic 25,26 Road Traffic Accidents (RTAs) V01-04, V06, V09-V79, V87, V89, V99 It would be expected that admissions due to RTAs would decrease during population level restrictions  in the patterns and trends observed between elective and emergency admissions, these are presented separately in Figure 3- Figure 5 and Figure 7. Trends in elective and emergency non COVID-19 hospital admission are shown in Figure 3 and Figure 4. Figure 5 outlines the results of the internal comparison within 2020 and shows reductions in Periods 2-4 2020 compared to Period 1 2020. Figure 8 shows reductions in non-COVID-19 hospital admissions for all admission types.
The greatest absolute and relative rate reductions were seen in Period 3 2020 compared to Period 1 2020 for the following:    Similar reductions were observed for both genders and across all age groups. The greatest relative rate reductions were in younger age groups (<45 years) while the greatest absolute rate reductions were seen in older age groups, particularly those aged over 80 years ( Tables A1-A3).

Trends in emergency department presentations and admissions
Analysis of ED activity indicated that a greater proportion of those presenting to ED in Periods 2-4 2020 were admitted and p-value <0.0001), followed by older age (AOR 5.00, 95% CI 4.84, 5.17, p-value <0.0001) were the greatest predictors of hospital admission from ED. Independent of other factors included in the model, there was an increased likelihood of being admitted to hospital following ED presentation in Periods 2-4 compared to Period 1, which was most marked in Period 3 (AOR, 1.10, 95% CI, 1.07, 1.12, p-value <0.0001). In the recovery period (Period 4), ED presentations a greater proportion of both presentations and admissions were from older age groups (p-value <0.0001), had arrived by ambulance (p-value <0.0001) and were admitted (p-value <0.0001) compared to Period 1 2020 (Table 4 and Table 5). Factors associated with conversion to hospital admission following presentation to ED were examined for their independent association through a logistic regression model (Table 6). Being in a higher triage category (AOR 8.88, 95% CI 8.64, 9.13,    and admissions from ED returned to pre-COVID-19 levels for those aged over 45 years but remained reduced for those aged below 45 years ( Figure 6).

Trends in non-COVID-19 hospital admissions
Analysis of non-COVID-19 hospital admissions using HIPE data found reductions across all diagnostic groups and all admission types including elective, emergency, maternity and newborn admissions ( Figure 8).
Trends in elective and emergency admissions for selected diagnostic groups are shown in Table 7. Comparing elective admissions in Periods 2-4 2020 to what would have been expected based on Period 1 2020, there were particularly large   (Table 8).          (Table 8).

Summary of key findings
This study reports on the changes in healthcare utilisation in acute hospitals in Ireland during the first wave of the COVID-19 pandemic in 2020. There was reduced healthcare utilisation for elective and emergency acute public hospital care. This reduction began in early March 2020, following the beginning of the first wave (Period 2), and overall persisted for the duration of this study which included the recovery period up to 5 th July 2020 (Period 4). During the recovery period, population rates of elective non-COVID-19 care did not recover. In contrast, there was greater recovery of emergency healthcare utilisation rates, however, activity still remained below pre COIVD-19 levels, particularly among younger age groups. In particular, this study finds evidence of increased emergency alcohol and emergency mental health related admissions in the recovery period (Period 4) which began with phase 1 of reopening of society on 18 th May 2020 until 5 th July 2020.
Those who presented to ED during the first wave of the COVID-19 pandemic had an increased likelihood of admission which may suggest increased severity of illness 27 . However, there is no evidence of an immediate increase in in-hospital mortality or an increase in co-morbidity on discharge. The full consequences of the impact of changes due to delayed or missed care on population health may only become apparent over time.

Comparison with other studies
The findings of this study are consistent with other published reports and literature describing disruption to healthcare services during the first wave of the COVID-19 pandemic in multiple countries 5,31-33 . In particular, reductions in ED presentations and hospital admissions which persisted following the easing of restrictions are reported 32-34 . While a proportion of these reductions were likely due to decreased incidence of certain conditions related to population-level restrictions, some necessary care was not accessed for acute medical emergencies (e.g., stroke and AMI) 3-5,32,35 . The greatest reductions in presentations were reported among vulnerable groups such as lower socioeconomic groups, those at extremes of age and ethnic minorities 5,36 .
This study found no evidence of immediate harm related to delayed or lost presentations. This is in contrast to other studies, which reported evidence of increased morbidity and mortality associated with changes in healthcare utilisation 4,5,37 . This impact may only become fully apparent over time and through examination of wider health information datasets.

Reasons for changes in acute hospital utilisation
The reasons for the changes in healthcare utilisation during the study period are likely multifactorial. The COVID-19 pandemic highlighted well-established weaknesses in the Irish health system that pre-date the COVID-19 pandemic. These include the absence of universal healthcare, acute hospital capacity deficits and a service configuration with overreliance on the acute hospital system to provide scheduled as well as unscheduled care due to poor orientation to primary and community care 7,10,11,38,39 . In order to create capacity to manage acute COVID-19 and non-COVID-19 illness, it was necessary to postpone elective care in the acute hospitals 38 . While some time-critical elective care was diverted to private hospitals 40 , analysis of clinical patterns of elective admissions in this study suggest that there are large backlogs in care. In the recovery period following the first wave of the COVID-19 pandemic in 2020, ongoing capacity restrictions in healthcare settings and the need to provide care for those with COVID-19 infection meant that it was not possible to resume elective activity at pre-COVID-19 levels or to provide the level of services required to fully address backlogs in elective care 41,42 . For emergency care, the reduction may have been due to reduced incidence of some medical conditions, e.g., injuries and non-COVID-19 infections, due to population-level restrictions and/or due to a reduction in unnecessary emergency attendances 26,35,43-48 . However, the scale of the reductions shown in this study and reduction in presentations for conditions such as stroke/TIA and AMI which are non-discretionary and time-sensitive suggest that necessary care was avoided or delayed. This may have been due to a fear of exposure to COVID-19 in hospital 49,50 . Increased utilisation of acute health services for emergency alcohol and self-harm admissions in the recovery period in wave 1 suggests that the pandemic, and associated restrictions, are negatively impacting population health and wellbeing. This finding is consistent with published data reporting increased mental distress and increased utilisation of secondary mental health services due to the COVID-19 pandemic 51-54 . This burden of unmet need is likely greatest among vulnerable groups most affected by COVID-19 such as those living in poverty, ethnic minority groups and older people 2,24,55-57 .

Implications for health policy and health system reform in Ireland
Harnessing the COVID-19 shock to manifest health system change. COVID-19 is a shock to the health system 58 . However, despite the challenges, the system has responded and shown innovation and flexibility in work practices and delivery of services, which demonstrate capacity and readiness to reform 11,38 . Lessons must be learned from COVID-19 to build health system resilience and increase preparedness for the future, including future pandemic preparedness 58,59 . In the long-term, further strategic reform aligned with Sláintecare should be progressed building on this innovation and change capability shown during the COVID-19 pandemic. Internationally, there have been calls to 'build back better' and also to 'build back fairer' to achieve sustainable, resilient health systems and deliver universal healthcare. Such an endeavour will require political leadership, human and financial resources and investment in information technology (IT) infrastructure and public health expertise 11,60-64 . The findings of this study were disseminated nationally to the director of Sláintecare and to the national leads for Integrated Care, the Acute Hospitals and Mental Health. This study quantified the changes in healthcare utilisation during the first wave of the COVID-19 pandemic and identified key clinical areas to focus on for population health recovery. The findings are important in the context of the ongoing reform of the Irish health system and the findings of this study informed the HSE National Service Plan for 2022 which has a focus on scheduled care recovery 65 .
Public health should be core to health reform. Public health has been frontline in confronting initial waves of COVID-19 in Ireland. With the development and arrival of the COVID-19 vaccination in 2021, Ireland has entered a new phase of the COVID-19 pandemic. However, COVID-19 and its associated consequences will continue to impact population health and the health system for many years. Therefore, strong public health leadership and advocacy are required to seize the opportunity to control COVID-19 infection, to guide population health recovery from COVID-19 and to progress health system reform in Ireland patterns observed in this study may predict healthcare utilisation in subsequent waves, there are likely differences as some lessons learned from the first wave may have been acted on. PET and HIPE datasets do not allow for identification of repeat episodes of care which may overestimate population rates of healthcare utilisation. However, such an overestimate is likely to be minimal due to the large size of the datasets. During the first wave of the COVID-19 pandemic, some time-sensitive elective care was provided in the private hospitals, these data were not available for this study. Therefore, the reduction in elective hospital activity may be overestimated. Data on GP utilisation were not analysed in this study, changes in provision of GP care may explain some of the changes reported. Hospital outpatient department (OPD) activity was also not examined, this may underestimate need for services as there are backlogs for OPD appointments. PET does not contain clinical information therefore the impact on non-COVID-19 care was not quantified. HIPE reports data on patients discharged from acute hospitals. Therefore, patients who remained in hospital at the end of the study period are not included in this study. As those who are more unwell may have longer admissions with poorer outcomes, co-morbidity and in-hospital mortality may have been underestimated.

Conclusion
This study quantifies and describes changes in acute hospital care utilisation during the first wave of the COVID-19 pandemic in Ireland. The results show that there are large backlogs in elective care, and evidence of delayed and lost emergency care. These backlogs in care must be managed with urgency. The consequences of delayed and lost care will only become fully apparent over time. The results also demonstrate increased population need and demand for mental health and alcohol services triggered by the pandemic. The population health impacts of COVID-19 and associated restrictions, particularly in relation to mental health and alcohol, need to be addressed through strong public health and health systems responses including the adoption of a pandemic recovery plan, especially targeting the most vulnerable. COVID-19 highlights inherent weakness in the Irish health system. However, the system shock is an opportunity to progress strategic reform of the Irish health system towards a universal, high-quality, sustainable and resilient health system, capable of meeting population health needs and responding to future pandemics. The datasets processed for this study were derived from special categories of personal data concerning health. The datasets are controlled by the HSE, not the authors, and so the authors cannot determine requests for data access. Further information on HSE data protection policy can be located at hse.ie/eng/gdpr/ hse-data-protection-policy/. Reasonable requests to access the two datasets used in this study, HIPE and PET, can be directed to the data controller by contacting the HSE Healthcare Pricing Office (https://hpo.ie/) in the case of HIPE and to the HSE Special Delivery Unit https://www.hse.ie/eng/about/who/ acute-hospitals-division/special-delivery-unit/ in the case of PET.

School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland
This is an interesting study showing some of the impacts of the pandemic on the Irish Health System. Whereas the authors have already addressed many issues raised by the other reviewers, an overall lack of context remains. The data sets used are from public hospitals only. One positive outcome of the pandemic was the use of private hospitals. They took over much of the elective and non-covid hospital care from the public hospitals. Whereas there is a mention in the limitations of the study, it should be better reflected in the whole manuscript. Reductions in noncovid admissions in the data may just be because these admissions happened in the private hospitals, not necessarily because they did not happen. This should be discussed in the results. It is now presented as if there just is a reduction due to the pandemic, which is true, but not the whole story. The reduction of 35% in non-covid admissions may be entirely explained by redirecting these to private hospitals.
The term recovery period is not appropriate. By July 2020 there was no recovery, in either healthcare use, the pandemic or otherwise. Please choose a better term throughout (or just stick with period 4).
Admission to hospitals changed radically during the pandemic, and most likely those who were sicker were more likely to be admitted. These people were sicker in general when they presented and therefore more likely to be admitted. What was not clear to me is if the fewer admissions were compared to the same period the previous year (which would be because of less presentations) or if this is a subset of the presentations. I suspect it is the first. If so, the figures should present the admissions as a subset of the total presentations, which could show that admissions from ED are actually higher.
The tracer conditions are of interest, as also pointed out by the other reviewers. In particular their rise in period 4. Whereas this is an interesting paper, the focus of the discussion is only on the reductions during period 2-3, while the tracer conditions and the potential of the health system to IRIS Centre, School of Nursing, Midwifery and Health Systems, University College Dublin, Dublin, Ireland Thank you for the revisions made in response to my comments. The title and methods now better reflect the content of the paper. Other alterations noted.

Is the work clearly and accurately presented and does it cite the current literature? Partly
Is the study design appropriate and is the work technically sound? Partly

If applicable, is the statistical analysis and its interpretation appropriate? Partly
Are all the source data underlying the results available to ensure full reproducibility? Partly

Are the conclusions drawn adequately supported by the results? Partly
This is an interesting paper using high quality national data on ED attendance and admissions at public hospitals in Ireland to identify how attendance/admissions altered over the initial weeks of the onset of COVID-19 in 2020.

Specific comments:
There is mention within the paper and in the abstract of interrupted time-trend analysis. I don't see this in the Results, so this reference needs to be amended. The logistic regression (Table 6) gives little insight on how predictors altered the likelihood of admission after Period 1. Consider re-focusing this regression -perhaps through this use of interactions, comparison with prior years, or a multinomial logit.

○
○ I think the discussion needs to better reflect the results. The most impactful finding of this paper is the lack of a rebound in hospital admissions for elective procedures in Period 4. While this is discussed in the Reasons for change in acute hospital utilisation section, it should also be clearly mentioned in the first paragraph of the Discussion: Summary of findings. This first paragraph also makes a statement suggesting evidence of increased severity in Periods 2 -4, however the triage classifications in the ED tables suggest little change in severity. Ambulance usage may have increased due to the restrictions on movement (lack of transport) and due to some individuals seeking guidance from paramedics on the need to attend hospital. Age may not be directly related to severity, an increase in the age of admissions may also be linked to a greater usage of ambulance. The Reasons for change in acute hospital utilisation section notes COVID-19 has highlighted the weaknesses in the Irish health system, and a number of references are given. I would recommend reviewing these references -a number pre-date COVID-19 and not all support that COVID-19 highlighted the shortcomings of the system. Perhaps rewording is needed here. ○ I would suggest reframing the title to match what the paper actually achieved. I don't feel the paper delivers on the title as currently stated, and I'm unsure what lessons derive directly from this analysis, for example I don't see the relationship with universal healthcare.

○
Overall, I think this is a good paper that presents a national picture that makes a valuable contribution to the literature.

Is the study design appropriate and is the work technically sound? Yes
Are sufficient details of methods and analysis provided to allow replication by others?

If applicable, is the statistical analysis and its interpretation appropriate? Yes
Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Partly Many thanks for your comments and feedback and for taking the time to review this paper.

Comment 1:
There is mention within the paper and in the abstract of interrupted time-trend analysis. I don't see this in the results so this reference needs to be amended.

Reply 1:
Thank you for your comment. This study was a comparison of population rates of healthcare utilisation during different time periods in the first wave of COVID-19 infection in Ireland in 2020; the time periods were defined based on the epidemiology of the first wave and the associated population level restrictions. It was described in the paper as an interrupted time-trend analysis. I have removed this term from the paper and abstract and I have updated the manuscript and described the study as a retrospective, population-based observational study which more accurately reflects the methodology. Table 1: the date range for Period 4 needs to be amended.

Reply 2:
Many thanks for flagging this error. I have amended this.

Comment 3:
Selecting the tracer diagnoses is valuable, perhaps this can be better motivated in the Outcomes section.

Reply 3:
Many thanks for this comment. I have added further information and detail to the outcomes section further explaining the purpose of selecting the tracer conditions, how the tracer conditions were selected and the rationale for their selection.

Comment 4:
The logistic regression (Table 6) gives little insight on how predictors altered the likelihood of admission after Period 1. Consider re-focusing this regression -perhaps through the use of interactions, comparison with prior years or a multinomial logit.

Reply 4:
Thank you for your comment. The purpose of the binary logistic regression analysis was to assess if presentation to ED within the specific time periods in the study was associated with an increased likelihood of admission from ED. The main finding was that independent of all other factors collected as part of PET data that may influence admission, there was an increased likelihood of being admitted to hospital following ED presentation in Periods 2-4 compared to Period 1, which was most marked in Period 3 (the peak of restrictions). Increased admissions from ED may suggest increased severity of illness on presentation (I have included a reference for this) and this was also in keeping with the clinical experience reported to the authors by clinicians at the time. I have edited the methods and the findings to more accurately reflect the purpose of the regression which has a limited impact on the overall findings of this paper.

Comment 5:
I think the discussion needs to better reflect the results. The most impactful finding of this paper is the lack of a rebound in hospital admissions for elective procedures in Period 4. While this is discussed in the Reasons for change in acute hospitalisation section, it should also be clearly mentioned in the first paragraph of the Discussion: Summary of findings. This first paragraph also makes a statement suggesting evidence of increased severity on Periods 2-4, however the triage classifications in the ED tables suggest little change in severity. Ambulance usage may have increased due to the restrictions on movement (lack of transport) and due to some individuals seeking guidance from paramedics on the need to attend hospital. Age may not be directly related to severity, an increase in the age of admissions may also be linked to a greater usage of ambulance. The Reasons for change in healthcare utilisation section notes that COVID-19 has highlighted the weaknesses in the Irish health system, and a number of references are given. I would recommend reviewing these references -a number pre-date COVID-19 and not all support that COVID-19 highlighted the shortcomings of the system. Perhaps rewording is needed here.

© 2021 Thavorn K.
This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Kednapa Thavorn
Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada This population-based study described the utilization of acute hospital services during the first wave of the COVID-19 pandemic in Ireland. The study was based on two national databases; ED attendances were obtained from Patient Experience Time (PET), while acute hospital discharge data were derived from Hospital In-Patient Enquiry (HIPE). Descriptive statistics and regression analysis were used to compare presentation to and admission from ED and acute hospital admission of any type for a non-COVID-19 illness across the four study periods, representing the epidemiology and public health management of COVID-19 in Ireland. This study shows that the first wave of COVID-19 was associated with decreased ED presentations, fewer admissions from ED, and non-COVID-19 hospital admissions. The study's title does not directly align with the study findings and is misleading. The study assessed the impact of the pandemic and the public health and health system measures on health care utilization; it did not fully describe how changes in health care utilization may affect public health or the health care system.

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There are some inconsistencies across the manuscript. In the abstract, the authors indicated that they used an interrupted time-series (ITS) analysis, but this methodology was not mentioned or used in the main texts. Instead, logistic regression was used. Please verify and ensure consistency. Additionally, the results section compared outcomes between four exposure periods and historical periods. The historical period was not defined or described in the method section. It is unclear why the first period (06/01/2020-01/03/2020) and the historical period (2017-19 or 2019) were used interchangeably as a reference group.

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What was the purpose of the inclusion of tracer diagnoses? Please provide further descriptions.

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The result section provides primarily descriptive results, which are difficult to interpret due to the potential impact of seasonal and trend patterns. If the authors did not use an ITS, they should focus on the results of multiple logistic regression analyses, as this method helped adjust for some confounding factors. The adjusted results would be more informative and more appropriate to compare against the existing literature.

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How were Figures 3 -7 generated? Were they based on multiple regression analyses? If they were, shouldn't the y-axis be shown as adjusted odd ratios instead of rate ratios? There were three study outcomes? Why were only the regression results of ED admission reported in the manuscript (Table 6)?

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The discussion on health policy and health system implications was too broad; it is unclear how the study findings led to these policy recommendations.
○ Is the work clearly and accurately presented and does it cite the current literature?
indicated that they used an interrupted time-series (ITS) analysis, but this methodology was not mentioned or used in the main texts. Instead, logistic regression was used. Please verify and ensure consistency. Additionally, the results section compared outcomes between four exposure periods and historical periods. The historical period was not defined or described in the method section. It is unclear why the first period (06/01/2020-01/03/2020) and the historical period (2017-19 or 2019) were used interchangeably as a reference group.

Reply 2:
Thank you for your comment. This was not an interrupted time series analysis and this term was not used in the manuscript. This study was a comparison of population rates of healthcare utilisation during different time periods in the first wave of COVID-19 infection in Ireland in 2020; the time periods were defined based on the epidemiology of the first wave and the associated population level restrictions. It was described in the paper as an interrupted time-trend analysis. On reflection, I agree that the term is unclear. Therefore, I have removed this term and I have described the study as a retrospective, population-based observational study which more accurately reflects the methodology. Thank you also for your comment regarding the need for more clarity about the historical reference periods and the reference period within 2020. I have included further details about this in the methodology and results sections. I have defined the time periods in the methods section and explained that both reference periods were used and the trends and associated public health implications were found to be similar so the paper primarily focuses on the internal comparison within 2020. The two comparisons showing similar trends also suggests that the variation observed within 2020 was not related only to seasonal differences in healthcare utilisation trends.

Comment 3:
What was the purpose of the inclusion of tracer diagnoses? Please provide further descriptions

Reply 3:
Thank you for your comment. I have provided further detail in the updated manuscript. The purpose of selecting the 'tracer diagnoses' was to explore healthcare utilisation trends in key clinical areas where changes in healthcare utilisation had been observed. These conditions were chosen following a review of the literature and from discussions with the national HSE Lead for Integrated Care, the Lead for the Acute Hospitals and for Mental Health who were clinicians providing frontline care during the COVID-19 pandemic in Ireland. Inclusion of the tracer diagnoses allowed us to better delineate more specific implications for key clinical conditions to inform recovery planning. I have included further detail on this in the outcomes section of the methods section.

Comment 4:
The result section provides primarily descriptive results, which are difficult to interpret due to the potential impact of seasonal and trend patterns. If the authors did not use an ITS, they should focus on the results of multiple logistic regression analyses, as this method helped adjust for some confounding factors. The adjusted results would be more informative and more appropriate to compare against the existing literature.

Reply 4:
Thank you for your comment. The results primarily focus on the absolute and relative differences in rates of healthcare utilisation in pre and post COVID-19 time periods. The purpose of including two reference periods was to assess if population trends in healthcare utilisation were similar for both periods, the historic (pre-2020) comparison allowed delineation of seasonal effects. Unfortunately, the logistic regression analysis could only be carried out for PET data as the HIPE data are aggregate data. I have stated this more clearly in the methods and I have included further detail on the logistic regression analysis. As outlined in the data sources section of the paper, HIPE is a well-established, quality-assured health information system that is the primary source of episode-based clinical, demographic and administrative data on discharges from acute public hospitals in Ireland. HIPE data are aggregate data that are used nationally to inform healthcare planning, management and activity-based funding. For this study the HIPE data provided details of non-COVID-19 admissions to the acute hospitals, it identified changes in trends for all non-COVID-19 admissions and in particular changes for elective and emergency admissions and differences in the changes observed between elective and emergency admissions.

Comment 5:
How were Figures 3 -7 generated? Were they based on multiple regression analyses? If they were, shouldn't the y-axis be shown as adjusted odd ratios instead of rate ratios? There were three study outcomes? Why were only the regression results of ED admission reported in the manuscript (Table 6)?

Reply 5:
Thank you for your comment. Figures 3 to 7 show the population rates of healthcare utilisation presented as weekly rates (Figures 3 and 4) and rate ratios ( Figures 5, 6 and 7). These figures were not generated from regression analysis but from calculation of population rates of healthcare utilisation and comparison between pre-and post-COVID-19 time periods. I have clarified this further in the methods and the axes of the figures are labelled to reflect what is shown. There were three study outcomes, outcome was a non-COVID-19 hospital admission. This outcome is reported in the results, the rate difference and rate ratio per 100,000 population. However, as the reductions in non-COVID-19 hospital admissions were predominantly for elective and emergency admissions and as there were notable differences in the patterns and trends observed between elective and emergency admissions, these are presented separately in Figures 3, 4 5 and 7. I have clarified this in the results section. Regression analysis was only possible for PET data which are individual level data while the HIPE data are episode based and are aggregate data. I have updated the data sources section of the paper to more clearly state this. The purpose of the regression analysis was to identify factors, including time period, on the likelihood of admission from ED following presentation to ED. I have amended the methods section to more accurately reflect the purpose of the regression analysis reported in Table 6.

Comment 6:
The discussion on health policy and health system implications was too broad; it is unclear how the study findings led to these policy recommendations.

Reply 6:
Thank you for your comment. I have changed the title of the paper. I have also updated the discussion to include that the findings of this study were disseminated nationally to the director of Sláintecare and to the national leads for integrated care, the acute hospitals and mental health. I have added that this study quantified the changes in healthcare utilisation during the first wave of the COVID-19 pandemic and identified key clinical areas to focus on for population health recovery which are important in the context of the ongoing reform of the Irish health system. I have also added that the findings of this study informed the HSE National Service Plan for 2022 which has a focus on scheduled care recovery with an included reference to the plan.
Competing Interests: I have no competing interests to declare.